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<h1 class="reftitle">mpt_call_gurobi</h1>
<h2>Purpose</h2>
<p>A gateway function to GUROBI solver (without errorchecks)</p>
<h2>Syntax</h2>
<pre class="synopsis">R = mpt_call_gurobi(S)</pre>
<h2>Description</h2>
<p></p>
        The function implements call to GUROBI solver based on formulation from <tt>Opt</tt> class.
        QP, LP, MILP and MIQP problems are supported.
        
        It is assumed that QP/LP/MIQP/MILP entering this function (for LP/MILP <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi1.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi1.png">)
        is of the form
        <p class="programlistingindent"><img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi16.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi16.png"></p>
        where the set <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi2.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi2.png"> represents
        <ul>
            
         <li>C - continuous variables, <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi3.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi3.png"> 
         </li>
            
         <li>I - integer variables <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi4.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi4.png"> 
         </li>
            
         <li>B - binary variables <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi5.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi5.png"> 
         </li>
            
         <li>N - semi-integer variables (possibly bounded above) <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi6.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi6.png"> 
         </li>
            
         <li>S - semi-continuous variables (possibly bounded above) <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi7.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi7.png"> 
         </li>
        
      </ul>
        which is given by strings in <tt>vartype</tt> field. GUROBI accepts this format directly, the
        only prerequisite is to transform input data to sparse format. 
                
	<h2>Input Arguments</h2>
<table cellspacing="0" class="body" cellpadding="4" border="0" width="100%">
<colgroup>
<col width="31%">
<col width="69%">
</colgroup>
<tbody><tr valign="top">
<td><tt>S</tt></td>
<td>
<p></p>Structure of the Opt class.<p>
	    		Class: <tt>struct</tt><p></p><tr valign="top">
<td><tt>S.H</tt></td>
<td>
<p></p>Quadratic part of the objective function.<p>
	    		Class: <tt>double</tt></p>
<p>
	    		Default: []</p>
</td>
</tr><tr valign="top">
<td><tt>S.f</tt></td>
<td>
<p></p>Linear part of the objective function.<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>S.A</tt></td>
<td>
<p></p>Linear part of the inequality constraints <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi8.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi8.png">.<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>S.b</tt></td>
<td>
<p></p>Right hand side of the inequality constraints <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi9.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi9.png">.<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>S.Ae</tt></td>
<td>
<p></p>Linear part of the equality constraints <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi10.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi10.png">.<p>
	    		Class: <tt>double</tt></p>
<p>
	    		Default: []</p>
</td>
</tr><tr valign="top">
<td><tt>S.be</tt></td>
<td>
<p></p>Right hand side of the equality constraints <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi11.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi11.png">.<p>
	    		Class: <tt>double</tt></p>
<p>
	    		Default: []</p>
</td>
</tr><tr valign="top">
<td><tt>S.lb</tt></td>
<td>
<p></p>Lower bound for the variables <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi12.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi12.png">.<p>
	    		Class: <tt>double</tt></p>
<p>
	    		Default: []</p>
</td>
</tr><tr valign="top">
<td><tt>S.ub</tt></td>
<td>
<p></p>Upper bound for the variables <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi13.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi13.png">.<p>
	    		Class: <tt>double</tt></p>
<p>
	    		Default: []</p>
</td>
</tr><tr valign="top">
<td><tt>S.n</tt></td>
<td>
<p></p>Problem dimension (number of variables).<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>S.m</tt></td>
<td>
<p></p>Number of inequalities in <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi14.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi14.png">.<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>S.me</tt></td>
<td>
<p></p>Number of equalities in <img src="../../../../fig/mpt/modules/solvers/mpt_call_gurobi15.png" alt="../../../../fig/mpt/modules/solvers/mpt_call_gurobi15.png">
            <p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>S.problem_type</tt></td>
<td>
<p></p>A string specifying the problem to be solved.<p>
	    		Class: <tt>char</tt></p>
</td>
</tr><tr valign="top">
<td><tt>S.vartype</tt></td>
<td>
<p></p>A string specifying the type of variable. Supported characters are
                C (continuous), I (integer), B (binary), N (semi-integer), S (semi-continuous). 
                Example: First variable from three is binary, the rest is continuous: <tt>S.vartype='BCC';</tt> 
                
            <p>
	    		Class: <tt>char</tt></p>
</td>
</tr><tr valign="top">
<td><tt>S.test</tt></td>
<td>
<p></p>Call (false) or not to call (true) MPT global settings.<p>
	    		Class: <tt>logical</tt></p>
<p>
	    		Default: false</p>
</td>
</tr><p></p></p>
</td>
</tr></tbody>
</table>
<h2>Output Arguments</h2>
<table cellspacing="0" class="body" cellpadding="4" border="0" width="100%">
<colgroup>
<col width="31%">
<col width="69%">
</colgroup>
<tbody><tr valign="top">
<td><tt>R</tt></td>
<td>
<p></p>result structure<p>
	    		Class: <tt>struct</tt><p></p><tr valign="top">
<td><tt>R.xopt</tt></td>
<td>
<p></p>optimal solution<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>R.obj</tt></td>
<td>
<p></p>Optimal objective value.<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>R.lambda</tt></td>
<td>
<p></p>Lagrangian multipliers.<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>R.exitflag</tt></td>
<td>
<p></p>An integer value that informs if the result was feasible (1), or otherwise (different from 1).<p>
	    		Class: <tt>double</tt></p>
</td>
</tr><tr valign="top">
<td><tt>R.how</tt></td>
<td>
<p></p>A string that informs if the result was feasible ('ok'), or if any problem appeared through optimization.<p>
	    		Class: <tt>char</tt></p>
</td>
</tr><p></p></p>
</td>
</tr></tbody>
</table>
<h2>References</h2>
<p class="citetitle">[1] 
	Stephen Boyd and Lieven Vandenberghe: Convex Optimization; Cambridge University Press
</p>
<h2>See Also</h2>
<a href="./mpt_solve.html">mpt_solve</a><p></p>
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<br><p>©  <b>2010-2013</b>     Martin Herceg: ETH Zurich,    <a href="mailto:herceg@control.ee.ethz.ch">herceg@control.ee.ethz.ch</a></p>
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